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DOI: 10.14569/IJACSA.2016.070339
PDF

Automation of Optimized Gabor Filter Parameter Selection for Road Cracks Detection

Author 1: Haris Ahmad Khan
Author 2: M. Salman
Author 3: Sajid Hussain
Author 4: Khurram Khurshid

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 3, 2016.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: Automated systems for road crack detection are extremely important in road maintenance for vehicle safety and traveler’s comfort. Emerging cracks in roads need to be detected and accordingly repaired as early as possible to avoid further damage thus reducing rehabilitation cost. In this paper, a robust method for Gabor filter parameters optimization for automatic road crack detection is discussed. Gabor filter has been used in previous literature for similar applications. However, there is a need for automatic selection of optimized Gabor filter parameters due to variation in texture of roads and cracks. The problem of change of background, which in fact is road texture, is addressed through a learning process by using synthetic road crack generation for Gabor filter parameter tuning. Tuned parameters are then tested on real cracks and a thorough quantitative analysis is performed for performance evaluation.

Keywords: Pavement Cracks; Automated detection; Gabor Filters; Genetic Algorithm; Parameter Selection

Haris Ahmad Khan, M. Salman, Sajid Hussain and Khurram Khurshid, “Automation of Optimized Gabor Filter Parameter Selection for Road Cracks Detection” International Journal of Advanced Computer Science and Applications(IJACSA), 7(3), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070339

@article{Khan2016,
title = {Automation of Optimized Gabor Filter Parameter Selection for Road Cracks Detection},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070339},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070339},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {3},
author = {Haris Ahmad Khan and M. Salman and Sajid Hussain and Khurram Khurshid}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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